*=========================================================================*
*	Gender-specific information on AI skill premiums: belief updating and behavioral responses
*	
*	4/20/2025
*	-------
*	Main Experiment Tables

*=========================================================================*

clear all
set more off

*cd
global path="D:\PhD\Research\AI_gender_gap"
cd $path
global data = "${path}\data"
global table = "${path}\results\table"
global figure = "${path}\results\figure"

graph set window fontface     "Times New Roman"
set scheme s1color

use "${data}\clean_data.dta",replace

global demo female age white married parental_status college fulltime low middle 
* ------------------------------------------------------------------------------
*                       supporting_table1
* ------------------------------------------------------------------------------
local vars "female age white married parental_status college fulltime low middle high "
estpost summarize `vars' 
esttab using supporting_table1.csv, cells("mean(fmt(3)) sd(fmt(3)) min(fmt(3)) max(fmt(3))") replace


* ------------------------------------------------------------------------------
*                       supporting_table2
* ------------------------------------------------------------------------------

balancetable (mean if group_assignment==1) (mean if group_assignment==2) (mean if group_assignment==3) (mean if group_assignment==4)  ///
female age white married parental_status college fulltime low middle high using "${table}/supporting_table2.xls",  pvalues vce(robust) replace ctitles("Control" "Female_only" "Male_only" "Both")

local vars "female age white married parental_status college fulltime low middle high "


    balancetable (mean if group_assignment==1) (mean if group_assignment==2) (mean if group_assignment==3) (mean if group_assignment==4) ///
        `vars' using "${table}/supporting_table2.xls", pvalues vce(robust) replace ctitles("Control" "Female only" "Male only" "Info both")
    * 打开 Excel 文件，添加表头并写入 p 值
    putexcel set "${table}/supporting_table2.xls", modify
    * 在 F1 添加表头 "P-value"
    putexcel F2 = "P-value"

* 计算 ANOVA p 值并追加到表格
    local row = 3  // 从第 2 行开始（假设第 1 行是标题）
    foreach var in `vars' {
        * 运行 ANOVA，限制在 g`i'==1 的子样本
        qui anova `var' group_assignment 
        * 计算 p 值
        local pval = Ftail(e(df_m), e(df_r), e(F))
        * 将 p 值写入 Excel 第 6 列（F 列）
        putexcel set "${table}/supporting_table2.xls", modify
        putexcel F`row' = `pval', nformat(0.###)  // 保留 4 位小数
        local row = `row' + 2
    }

	

* ------------------------------------------------------------------------------
*                       supporting_table3
* ------------------------------------------------------------------------------

* 定义变量列表
local varlist ai_premium_f_p ai_premium_m_p usai_skill_premium_f usai_skill_premium_m 

* 变量标签（美化显示，修复引号问题）
local varnames "Woman Man Woman Man"

* 初始化 Excel
putexcel set "${table}/descriptive_stats.xlsx", replace sheet("Table 1")
putexcel A1 = "Table 1: Descriptive Statistics by Gender", bold
putexcel A2 = "Variable" B2 = "All Mean" C2 = "Female Mean" D2 = "Male Mean" E2 = "p-value", bold

* 插入面板标题
putexcel A3 = "Panel A: Predicted AI Premiums in Norway", bold
putexcel A7 = "Panel B: Predicted AI Premiums in US", bold

* 初始化行号
local rows 4 5 8 9   // 变量行
local vert_rows 6 10   // 纵向 p 值行
local panel_rows 3 7   // 面板标题行

* 循环计算均值和横向 p 值
local i = 1
foreach var in `varlist' {
    if inlist("`var'", "usai_skill_premium_f", "usai_skill_premium_m") {
        * 全样本均值 (仅对 usai 变量限制 group_assignment==1)
        quietly summarize `var' if group_assignment==1, meanonly
        local mean_all = r(mean)
        local mean_all: di %4.3f `mean_all'
        
        * 女性均值
        quietly summarize `var' if female == 1 & group_assignment==1, meanonly
        local mean_f = r(mean)
        local mean_f: di %4.3f `mean_f'
        local n_f = r(N)
        
        * 男性均值
        quietly summarize `var' if female == 0 & group_assignment==1, meanonly
        local mean_m = r(mean)
        local mean_m: di %4.3f `mean_m'
        local n_m = r(N)
        
        * 横向 t 检验
        quietly ttest `var' if group_assignment==1, by(female)
        local p_horiz = r(p)
        local p_horiz: di %4.3f `p_horiz'
        local star_horiz = cond(`p_horiz' < 0.1, "*", cond(`p_horiz' < 0.05, "**", cond(`p_horiz' < 0.01, "***", "")))
    }
    else {
        * 全样本均值 (对 ai_premium 变量不限制 group_assignment)
        quietly

 summarize `var', meanonly
        local mean_all = r(mean)
        local mean_all: di %4.3f `mean_all'
        
        * 女性均值
        quietly summarize `var' if female == 1, meanonly
        local mean_f = r(mean)
        local mean_f: di %4.3f `mean_f'
        local n_f = r(N)
        
        * 男性均值
        quietly summarize `var' if female == 0, meanonly
        local mean_m = r(mean)
        local mean_m: di %4.3f `mean_m'
        local n_m = r(N)
        
        * 横向 t 检验
        quietly ttest `var', by(female)
        local p_horiz = r(p)
        local p_horiz: di %4.3f `p_horiz'
        local star_horiz = cond(`p_horiz' < 0.1, "*", cond(`p_horiz' < 0.05, "**", cond(`p_horiz' < 0.01, "***", "")))
    }
    
    * 获取变量名称
    local varname: word `i' of `varnames'
    
    * 写入均值和横向 p 值
    local row: word `i' of `rows'
    putexcel A`row' = "`varname'"
    putexcel B`row' = `mean_all'
    putexcel C`row' = `mean_f'
    putexcel D`row' = `mean_m'
    putexcel E`row' = "`p_horiz'`star_horiz'"
    
    local i = `i' + 1
}

* 纵向 t 检验（配对变量，修复引号问题）
local pairs "ai_premium_f_p ai_premium_m_p usai_skill_premium_f usai_skill_premium_m"

local j = 1
local k = 1
foreach pair in `pairs' {
    if mod(`k', 2) == 1 {
        local var1 `pair'
    }
    else {
        local var2 `pair'
        
        if inlist("`var1'", "usai_skill_premium_f") {
            * 全样本纵向 t 检验 (仅对 usai 变量限制 group_assignment==1)
            quietly ttest `var1' = `var2' if group_assignment==1
            local p_vert_all = r(p)
            local p_vert_all: di %4.3f `p_vert_all'
            local star_vert_all = cond(`p_vert_all' < 0.1, "*", cond(`p_vert_all' < 0.05, "**", cond(`p_vert_all' < 0.01, "***", "")))
            
            * 女性纵向 t 检验
            quietly ttest `var1' = `var2' if female == 1 & group_assignment==1
            local p_vert_f = r(p)
            local p_vert_f: di %4.3f `p_vert_f'
            local star_vert_f = cond(`p_vert_f' < 0.1, "*", cond(`p_vert_f' < 0.05, "**", cond(`p_vert_f' < 0.01, "***", "")))
            
            * 男性纵向 t 检验
            quietly ttest `var1' = `var2' if female == 0 & group_assignment==1
            local p_vert_m = r(p)
            local p_vert_m: di %4.3f `p_vert_m'
            local star_vert_m = cond(`p_vert_m' < 0.1, "*", cond(`p_vert_m' < 0.05, "**", cond(`p_vert_m' < 0.01, "***", "")))
        }
        else {
            * 全样本纵向 t 检验 (对 ai_premium 变量不限制 group_assignment)
            quietly ttest `var1' = `var2'
            local p_vert_all = r(p)
            local p_vert_all: di %4.3f `p_vert_all'
            local star_vert_all = cond(`p_vert_all' < 0.1, "*", cond(`p_vert_all' < 0.05, "**", cond(`p_vert_all' < 0.01, "***", "")))
            
            * 女性纵向 t 检验
            quietly ttest `var1' = `var2' if female == 1
            local p_vert_f = r(p)
            local p_vert_f: di %4.3f `p_vert_f'
            local star_vert_f = cond(`p_vert_f' < 0.1, "*", cond(`p_vert_f' < 0.05, "**", cond(`p_vert_f' < 0.01, "***", "")))
            
            * 男性纵向 t 检验
            quietly ttest `var1' = `var2' if female == 0
            local p_vert_m = r(p)
            local p_vert_m: di %4.3f `p_vert_m'
            local star_vert_m = cond(`p_vert_m' < 0.1, "*", cond(`p_vert_m' < 0.05, "**", cond(`p_vert_m' < 0.01, "***", "")))
        }
        
        * 写入纵向 p 值（第二行下方）
        local vert_row: word `j' of `vert_rows'
        putexcel A`vert_row' = "p-value", italic
        putexcel B`vert_row' = "`p_vert_all'`star_vert_all'"
        putexcel C`vert_row' = "`p_vert_f'`star_vert_f'"
        putexcel D`vert_row' = "`p_vert_m'`star_vert_m'"
        
        local j = `j' + 1
    }
    local k = `k' + 1
}

* 计算总样本量
quietly count
local n_all_total = r(N)
quietly count if female == 1
local n_f_total = r(N)
quietly count if female == 0
local n_m_total = r(N)

* 写入脚注
putexcel A12 = "Notes:", bold
putexcel A13 = "Means are reported with 3 decimal places. * p < 0.1, ** p < 0.05, *** p < 0.01."
putexcel A14 = "Observations: All (N = `n_all_total'), Female (N = `n_f_total'), Male (N = `n_m_total')."

* 关闭 Excel
putexcel close


********************************************************************************
* ------------------------------------------------------------------------------
* 定义变量列表
local varlist ai_premium_f_p ai_premium_m_p usai_skill_premium_f usai_skill_premium_m ///
              confidence_guess_female_numeric confidence_guess_male_numeric ///
              usconfidence_female_numeric usconfidence_male_numeric

* 变量标签（美化显示，修复引号问题）
local varnames "Norway Female AI Premium Norway Male AI Premium US Female AI Premium US Male AI Premium Confidence Norway Female Confidence Norway Male Confidence US Female Confidence US Male"

* 初始化 Excel
putexcel set "${table}/descriptive_stats.xlsx", replace sheet("Table 1")
putexcel A1 = "Table 1: Descriptive Statistics by Gender", bold
putexcel A2 = "Variable" B2 = "All Mean" C2 = "Female Mean" D2 = "Male Mean" E2 = "p-value", bold

* 插入面板标题
putexcel A3 = "Panel A: Predicted AI Premiums in Norway", bold
putexcel A7 = "Panel B: Confidence in Predicted AI Premiums in Norway", bold
putexcel A11 = "Panel C: Predicted AI Premiums in US", bold
putexcel A15 = "Panel D: Confidence in Predicted AI Premiums in US", bold

* 初始化行号
local rows 4 5 8 9 12 13 16 17  // 变量行
local vert_rows 6 10 14 18  // 纵向 p 值行
local panel_rows 3 7 11 15  // 面板标题行

* 循环计算均值和横向 p 值
local i = 1
foreach var in `varlist' {
    * 全样本均值
    quietly summarize `var' if group_assignment==1, meanonly
    local mean_all = r(mean)
    local mean_all: di %4.3f `mean_all'
    
    * 女性均值
    quietly summarize `var' if female == 1 & group_assignment==1, meanonly
    local mean_f = r(mean)
    local mean_f: di %4.3f `mean_f'
    local n_f = r(N)
    
    * 男性均值
    quietly summarize `var' if female == 0 & group_assignment==1, meanonly
    local mean_m = r(mean)
    local mean_m: di %4.3f `mean_m'
    local n_m = r(N)
    
    * 横向 t 检验
    quietly ttest `var' if group_assignment==1, by(female)
    local p_horiz = r(p)
    local p_horiz: di %4.3f `p_horiz'
    local star_horiz = cond(`p_horiz' < 0.1, "*", cond(`p_horiz' < 0.05, "**", cond(`p_horiz' < 0.01, "***", "")))
    
    * 获取变量名称
    local varname: word `i' of `varnames'
    
    * 写入均值和横向 p 值
    local row: word `i' of `rows'
    putexcel A`row' = "`varname'"
    putexcel B`row' = `mean_all'
    putexcel C`row' = `mean_f'
    putexcel D`row' = `mean_m'
    putexcel E`row' = "`p_horiz'`star_horiz'"
    
    local i = `i' + 1
}

* 纵向 t 检验（配对变量，修复引号问题）
local pairs "ai_premium_f_p ai_premium_m_p usai_skill_premium_f usai_skill_premium_m confidence_guess_female_numeric confidence_guess_male_numeric usconfidence_female_numeric usconfidence_male_numeric"

local j = 1
local k = 1
foreach pair in `pairs' {
    if mod(`k', 2) == 1 {
        local var1 `pair'
    }
    else {
        local var2 `pair'
        
        * 全样本纵向 t 检验
        quietly ttest `var1' = `var2' if group_assignment==1
        local p_vert_all = r(p)
        local p_vert_all: di %4.3f `p_vert_all'
        local star_vert_all = cond(`p_vert_all' < 0.1, "*", cond(`p_vert_all' < 0.05, "**", cond(`p_vert_all' < 0.01, "***", "")))
        
        * 女性纵向 t 检验
        quietly ttest `var1' = `var2' if female == 1 & group_assignment==1
        local p_vert_f = r(p)
        local p_vert_f: di %4.3f `p_vert_f'
        local star_vert_f = cond(`p_vert_f' < 0.1, "*", cond(`p_vert_f' < 0.05, "**", cond(`p_vert_f' < 0.01, "***", "")))
        
        * 男性纵向 t 检验
        quietly ttest `var1' = `var2' if female == 0 & group_assignment==1
        local p_vert_m = r(p)
        local p_vert_m: di %4.3f `p_vert_m'
        local star_vert_m = cond(`p_vert_m' < 0.1, "*", cond(`p_vert_m' < 0.05, "**", cond(`p_vert_m' < 0.01, "***", "")))
        
        * 写入纵向 p 值（第二行下方）
        local vert_row: word `j' of `vert_rows'
        putexcel A`vert_row' = "p-value", italic
        putexcel B`vert_row' = "`p_vert_all'`star_vert_all'"
        putexcel C`vert_row' = "`p_vert_f'`star_vert_f'"
        putexcel D`vert_row' = "`p_vert_m'`star_vert_m'"
        
        local j = `j' + 1
    }
    local k = `k' + 1
}

* 计算总样本量
quietly count
local n_all_total = r(N)
quietly count if female == 1
local n_f_total = r(N)
quietly count if female == 0
local n_m_total = r(N)

* 写入脚注
putexcel A17 = "Notes:", bold
putexcel A18 = "Means are reported with 3 decimal places. p-values in the table are from two-sample t-tests comparing female and male means. Vertical p-values (below variable pairs) are from paired t-tests within each group (All, Female, Male). * p < 0.1, ** p < 0.05, *** p < 0.01."
putexcel A19 = "Sample includes participants from a controlled experiment on AI skill premiums. Observations: All (N = `n_all_total'), Female (N = `n_f_total'), Male (N = `n_m_total')."

* 关闭 Excel
putexcel close


ttest usai_skill_premium_m if group_assignment==1, by(female)



* ------------------------------------------------------------------------------
*                       supporting_table4

*Treatment effect on predicted AI skill premiums in U.S. labor market
* ------------------------------------------------------------------------------
* ------------------------------------------------------------------------------
*       				对美国的预测
* ------------------------------------------------------------------------------

reg usai_skill_premium_f Female_only Male_only Both ai_premium_f_p ai_premium_m_p $demo if female==1, vce(r) 
lincom Both-Female_only
lincom Both-Male_only
lincom Male_only-Female_only
est store a1

reg usai_skill_premium_f Female_only Male_only Both ai_premium_f_p ai_premium_m_p $demo if female==0, vce(r) 
lincom Both-Female_only
lincom Both-Male_only
lincom Male_only-Female_only
est store a2

reg usai_skill_premium_m Female_only Male_only Both ai_premium_f_p ai_premium_m_p $demo if female==1, vce(r) 
lincom Both-Female_only
lincom Both-Male_only
lincom Male_only-Female_only
est store a3

reg usai_skill_premium_m Female_only Male_only Both ai_premium_f_p ai_premium_m_p $demo if female==0, vce(r) 
lincom Both-Female_only
lincom Both-Male_only
lincom Male_only-Female_only
est store a4


reg usdiff Female_only Male_only Both ai_premium_f_p ai_premium_m_p $demo if female==1, vce(r) 
lincom Both-Female_only
lincom Both-Male_only
lincom Male_only-Female_only
est store a5

reg usdiff Female_only Male_only Both ai_premium_f_p ai_premium_m_p $demo if female==0, vce(r) 
lincom Both-Female_only
lincom Both-Male_only
lincom Male_only-Female_only
est store a6


// 输出表格，添加控制组均值
outreg2 [a1 a2 a3 a4 a5 a6] using ${table}/supporting_table4.xls, excel bdec(3)   ///
    keep(Female_only Male_only Both)  ///
    addtext(Baseline beliefs, Yes, Controls, Yes) nocons replace ///         
    alpha(0.001, 0.01, 0.05)   


		
* ------------------------------------------------------------------------------
*         supporting_table5        

* Treatment effect on personal labor market outcomes
* ------------------------------------------------------------------------------	
rename ai_employment_opportunities ai_employment_opp

foreach var in ai_competitive ai_employment_opp ai_salary_opportunities {
	
	norm `var', method(zee) 
} 

est clear
reg zee_ai_competitive Female_only Male_only Both ai_premium_f ai_premium_m ai_competitive_pre $demo if female==1, r
est store a1

reg zee_ai_employment_opp Female_only Male_only Both ai_premium_f ai_premium_m ai_employment_opportunities_pre $demo if female==1, r
est store a2

reg zee_ai_salary_opportunities Female_only Male_only Both ai_premium_f ai_premium_m ai_salary_opportunities_pre $demo if female==1, r
est store a3

reg zee_ai_competitive Female_only Male_only Both ai_premium_f ai_premium_m ai_competitive_pre $demo if female==0, r
est store a4

reg zee_ai_employment_opp Female_only Male_only Both ai_premium_f ai_premium_m ai_employment_opportunities_pre $demo if female==0, r
est store a5

reg zee_ai_salary_opportunities Female_only Male_only Both ai_premium_f ai_premium_m ai_salary_opportunities_pre $demo if female==0, r
est store a6

outreg2 [a*] using ${table}/supporting_table5.xls, excel  bdec(3)   ///
    keep(Female_only Male_only Both) ///
    addtext(Baseline beliefs, Yes, Controls, Yes) nocons replace  ///         
    alpha(0.001, 0.01, 0.05)   
	
	
* ------------------------------------------------------------------------------
*         supporting_table6       

* Treatment effect on the willingness and actual use of AI tools
* ------------------------------------------------------------------------------	
rename ai_subscription_willingness ai_sub
foreach var in ai_interest ai_willingness ai_sub {
	
	norm `var', method(zee) 
	
} 

est clear

reg zee_ai_willingness Female_only Male_only Both ai_premium_f ai_premium_m ai_willingness_pre $demo if female==1,r
est store a1

reg zee_ai_sub Female_only Male_only Both ai_premium_f ai_premium_m ai_subscription_willingness_pre $demo if female==1,r
est store a2

reg register Female_only Male_only Both ai_premium_f ai_premium_m  $demo if female==1,r
est store a3

***

reg zee_ai_willingness Female_only Male_only Both ai_premium_f ai_premium_m ai_willingness_pre $demo if female==0,r
est store a4

reg zee_ai_sub Female_only Male_only Both ai_premium_f ai_premium_m ai_subscription_willingness_pre $demo if female==0,r
est store a5

reg register Female_only Male_only Both ai_premium_f ai_premium_m  $demo if female==0,r
est store a6

outreg2 [a*] using ${table}/supporting_table6.xls, excel  bdec(3)   ///
    keep(Female_only Male_only Both) ///
    addtext(Baseline beliefs, Yes, Controls, Yes) nocons replace ///         
    alpha(0.001, 0.01, 0.05)   
	
* ------------------------------------------------------------------------------
*         supporting_table7       

* Treatment effect on demand for AI training
* ------------------------------------------------------------------------------		

foreach var in ai_course_interest {
	
	norm `var', method(zee) 
	
} 



reg zee_ai_course_interest Female_only Male_only Both ai_premium_f ai_premium_m ai_course_interest_pre $demo  if female==1,r
est store a1

reg risk_switch_course_new Female_only Male_only Both ai_premium_f ai_premium_m risk_switch $demo if female==1,r
est store a2

***
reg zee_ai_course_interest Female_only Male_only Both ai_premium_f ai_premium_m ai_course_interest_pre  $demo if female==0,r
est store a3

reg risk_switch_course_new Female_only Male_only Both ai_premium_f ai_premium_m risk_switch $demo if female==0 ,r
est store a4	
	
outreg2 [a1 a2 a3 a4] using ${table}/supporting_table7.xls, excel  bdec(3)   ///
    keep(Female_only Male_only Both) ///
    addtext(Baseline beliefs, Yes, Controls, Yes) nocons replace  ///         
    alpha(0.001, 0.01, 0.05)   	
	
	
* ------------------------------------------------------------------------------
*         supporting_table8      

* Heterogeneity of treatment effects by fairness concern
* ------------------------------------------------------------------------------	

reg zee_ai_competitive c.Female_only##c.ai_skill_fairness  c.Male_only##c.ai_skill_fairness c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p ai_competitive_pre $demo, r
estimates store z1

reg zee_ai_employment_opp c.Female_only##c.ai_skill_fairness  c.Male_only##c.ai_skill_fairness c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p ai_employment_opportunities_pre $demo, r
estimates store z2

reg zee_ai_salary_opportunities c.Female_only##c.ai_skill_fairness  c.Male_only##c.ai_skill_fairness c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p ai_salary_opportunities_pre $demo, r
estimates store z3

reg zee_ai_willingness c.Female_only##c.ai_skill_fairness  c.Male_only##c.ai_skill_fairness c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p ai_willingness_pre $demo, r
estimates store z4

reg zee_ai_sub c.Female_only##c.ai_skill_fairness  c.Male_only##c.ai_skill_fairness c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p ai_subscription_willingness_pre $demo, r
estimates store z5

reg register c.Female_only##c.ai_skill_fairness  c.Male_only##c.ai_skill_fairness c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p $demo, r
estimates store z6

outreg2 [z*] using ${table}/supporting_table8.xls, excel  bdec(3)   ///
    keep(c.Female_only##c.ai_skill_fairness c.Male_only##c.ai_skill_fairness c.Both##c.ai_skill_fairness) sortvar(ai_skill_fairness Female_only Male_only Both c.Female_only#c.ai_skill_fairness c.Male_only#c.ai_skill_fairness c.Both#c.ai_skill_fairness) ///
    addtext(Baseline beliefs, Yes, Controls, Yes) nocons replace   ///         
    alpha(0.001, 0.01, 0.05)   	
	
* ------------------------------------------------------------------------------
*         supporting_table8      

* Heterogeneity of treatment effects by fairness concern
* ------------------------------------------------------------------------------	

reg zee_ai_competitive Female_only Male_only c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p ai_competitive_pre $demo, r
estimates store z1

reg zee_ai_employment_opp Female_only Male_only c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p ai_employment_opportunities_pre $demo, r
estimates store z2

reg zee_ai_salary_opportunities Female_only Male_only c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p ai_salary_opportunities_pre $demo, r
estimates store z3

reg zee_ai_willingness Female_only Male_only c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p ai_willingness_pre $demo, r
estimates store z4

reg zee_ai_sub Female_only Male_only c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p ai_subscription_willingness_pre $demo, r
estimates store z5

reg register Female_only Male_only c.Both##c.ai_skill_fairness ai_premium_f_p ai_premium_m_p $demo, r
estimates store z6

outreg2 [z*] using ${table}/supporting_table8.xls, excel  bdec(3)   ///
    keep(Female_only Male_only c.Both##c.ai_skill_fairness) sortvar(ai_skill_fairness Female_only Male_only Both c.Both#c.ai_skill_fairness) ///
    addtext(Baseline beliefs, Yes, Controls, Yes) nocons replace	
	